Browsing by Author "Aljohani, Mohammed"

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EARNED INCOME TAX CREDIT 2009 EXPANSION: A NATIONAL AND STATE-LEVEL ANALYSIS OF CHILD POVERTY REDUCTION, TAX RETURNS, AND INFLATION-ADJUSTED BENEFITS, 2000-2022
(ProQuest Dissertations & Theses, 2025) Aljohani, Mohammed; Gilleylen, Johnny
This study investigates the impact of the Earned Income Tax Credit (EITC) 2009 on child poverty in the U.S. Census Bureau data shows child poverty has increased by 0.29 points each year, starting at 16.20 percent in 2000 to 19.00 percent in 2008. States with the highest child poverty rates, such as Mississippi (28.08 percent), Louisiana (26.67 percent), New Mexico (25.23 percent), Arkansas (23.86 percent), and West Virginia (23.78 percent), exceed the national average of 17.62 percent for those years. Prior research found that childhood poverty negatively affects the economy, health, and education. Previous research on the impact of the 2009 EITC policy change on child poverty reduction in the U.S.—including metrics such as EITC claims, average credit per household, and inflation-adjusted benefits—has been limited or inconclusive. This study investigates the effects of the EITC provisions introduced through the American Recovery and Reinvestment Act of 2009 on the U.S. child poverty. It also focuses on state-level EITC tax returns and average credit amounts in the five states with the highest and lowest child poverty rates, using a quantitative approach that combines interrupted time series and cross-sectional research designs with data from the U.S. Census Bureau and the IRS. Since 2000, the EITC has helped lift an average of 2.36 million children out of poverty each year. A 2009 policy change boosted that number by 21 percent, with 2.52 million children lifted annually. However, the impact declined during COVID-19, with noticeable drops in EITC claims, credits, and adjusted benefits. The 2009 expansion led to increased EITC use across both high- and low-poverty states, with the greatest gains seen in the most disadvantaged states— contradicting key assumptions of social construction theory. At the end, the study offers policy recommendations to enhance EITC’s equity and effectiveness.
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IPO Governance in Saudi Arabia's Energy Sector: Legal Structures, Compliance, and Reform under Vision 2030
(Saudi Digital Library, 2025) Aljohani, Mohammed; Nigro, Casimiro
This thesis examines the legal and institutional dimensions of initial public offerings (IPOs) in Saudi Arabia’s energy sector, with a focus on how corporate governance, compliance, and ESG mechanisms are formalized within state-owned enterprises (SOEs) undergoing partial market exposure. IPOs in this context are not solely financial transactions but are also instruments of institutional transformation—tools that enable alignment with international standards while accommodating sovereign policy priorities. Employing a doctrinal legal methodology supported by a case study of Saudi Aramco, the research investigates how statutory provisions, Capital Market Authority regulations, and corporate governance codes shape the IPO process, particularly in relation to board independence, disclosure obligations, and sustainability oversight. The findings reveal that although the Saudi regulatory framework demonstrates formal convergence with global governance norms, its implementation reflects selective adaptation, shaped by the continued presence of state ownership through entities such as the Public Investment Fund. The thesis further explores how IPO governance structures are designed to advance transparency, investor confidence, and ESG integration, while retaining flexibility for national development strategies under Vision 2030. In doing so, it contributes to corporate governance literature by offering a nuanced understanding of hybrid regulatory models, where public-sector priorities and market-facing reforms coexist. Ultimately, the study argues that IPOs in Saudi Arabia’s energy sector function as calibrated mechanisms of governance modernization, balancing legal compliance, institutional credibility, and sovereign interests, rather than serving as vehicles of full privatization or market liberalization.
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The Impact of LLMs Usage on Learning Outcomes for Software Development Students: A Focus on Prompt Engineering
(Saudi Digital Library, 2025) Aljohani, Mohammed; Itamar Shabtai; June K. Hilton; Chinazunwa Uwaoma
This study investigates the impact of large language model (LLM) usage, specifically ChatGPT, on student learning outcomes in programming education. The research adopts a mixed-methods approach, combining quantitative survey data from students and qualitative interviews with instructors. The study addresses three research questions: (1) the effect of LLM usage on undergraduate students' learning outcomes, (2) the influence of prompt engineering skills on this relationship, and (3) instructors' perceptions on these relationships. Quantitative data were collected from 159 students across two Saudi universities using a structured online survey with sections covering demographic information, LLM usage, self-reported programming understanding, and prompt engineering skills. Qualitative data were obtained through semi-structured interviews with programming instructors, covering LLM usage, prompt engineering skills, and their impact on student learning outcomes. The quantitative analysis utilized Partial Least Squares Structural Equation Modeling (PLS-SEM) to assess the measurement and structural models, including path coefficients, model explanatory power (R²), and predictive power (PLSpredict). Qualitative data were thematically analyzed using Atlas.ti to identify key themes related to instructor perspectives on the model. LLM usage positively impacts learning outcomes. While quantitative results did not show a significant moderating effect of prompt engineering skills, qualitative findings highlight its critical role in determining the positive effect of LLM usage on learning outcomes. The study emphasizes the importance of clear LLM usage policies and early prompt engineering training to promote meaningful engagement and maintain academic integrity in programming courses.
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